Pr. CESARE ALIPPI
Politecnico di Milano, Italy
Universita' della Svizzera italiana
Title : "Neural Graph Processing"
Many fields, like physics, neuroscience, chemistry, and sociology, investigate phenomena by processing multivariate measurementsadvantageously represented as a sequence of attributed graphs. Graphs come in different forms, with variable attributes, topology, and ordering, making it difficult to perform a mathematical analysis in the graph space. Within this framework, we are interested in processing graph datastreams to solve applications e.g., detect structural changes in the graphsequence, a situation associated with time variance, faults, anomalies or events of interestas well as design sophisticated processing like those requested by predictors. On the change detection front, theoretic results show that, under mild hypotheses, the confidence level of an event detected in the graph domain can be associated with another confidence level inan embedding space; this enables the identification of events in the graph domain by investigating embedded data. The opposite holds. However, evaluation of distances between graphs and identification of an appropriate embedding for the problem at hand are far from being trivial tasks with deep adversarial learning approaches and constant curvature manifold transformation showing to be appropriate transformations able to solve the problem. Deep autoregressive predictive models can then be designed to operate directly on graphs, hence providing the building blocks for other future sophisticated neural processing.
CESARE ALIPPI received the degree in electronic engineering cum laude in 1990 and the PhD in 1995 from Politecnico di Milano, Italy. Currently, he is a Professor with the Politecnico di Milano, Milano, Italy and Università della Svizzera italiana, Lugano, Switzerland. He is a visiting professor at the University of Kobe, Japan, the University of Guangzhou, China and Consultant Professor at the Northwestern Polytechnic in Xi’An, China. He has been a visiting researcher at UCL (UK), MIT (USA), ESPCI (F), CASIA (RC), A*STAR (SIN). Alippi is an IEEE Fellow, Member of the Administrative Committee of the IEEE Computational Intelligence Society, Board of Governors member of the International Neural Network Society, Board of Directors member of the European Neural Network Society, Past Vice-President education of the IEEE Computational Intelligence Society , past associate editor of the IEEE Transactions on Emerging topics in computational intelligence, the IEEE Computational Intelligence Magazine, the IEEE-Transactions on Instrumentation and Measurements , the IEEE-Transactions on Neural Networks. In 2018 he received IEEE CIS Outstanding Computational Intelligence Magazine Award , the 2016 Gabor award from the International Neural Networks Society and the IEEE Computational Intelligence Society Outstanding Transactions on Neural Networks and Learning Systems Paper Award ; in 2013 the IBM Faculty award ; in 2004 the IEEE Instrumentation and Measurement Society Young Engineer Award. Current research activity addresses adaptation and learning in non-stationary environments, graph learning and Intelligence for embedded, IoT and cyber-physical systems . He holds 8 patents, has published one monograph book, 7 edited books and about 200 papers in international journals and conference proceedings.
Pr. Reda ALHAJJ
The University of Calgary,Alberta Canada
Title : "Effectiveness of Data Science for Vital Applications: From Healthcare to Homeland Security"
The rapid development in technology and social media has gradually shifted the focus in research, industry and the community from traditional onto dynamic environments where creativity and innovation dominate various aspects of the daily life. This facilitated the automated collection and storage of huge amount of data which is necessary for effective decision making. The value of data is increasingly realized and there is a tremendous need for effective techniques to maintainand handle the collected data starting from storage to processing and analysis leading to knowledge discovery.This talk will focus ontechniques and structures which could maximize the benefit from data beyond what is traditionally supported. We emphasize data intensive domains, including healthcare and homeland security, which require developing and utilizing advance computational techniques for informative discoveries.We describe some of our accomplishments, ongoing research and future research plans. The notion of big data will be addressed to show how it is possible to process incrementally availablebig data using limited computing resources. The benefit of various data mining and network modeling mechanisms for data analysis and prediction will be addressed leading to collaborative decision making and shaping of future plans.
Reda Alhajj is a professor in the Department of Computer Science at the University of Calgary. He published over 500 papers in refereed international journals, conferences and edited books. He served on the program committee of several international conferences. He is founding editor in chief of the Springer premier journal “Social Networks Analysis and Mining”, founding editor-in-chief of Springer Series “Lecture Notes on Social Networks”, founding editor-in-chief of Springer journal “Network Modeling Analysis in Health Informatics and Bioinformatics”, founding co-editor-in-chief of Springer “Encyclopedia on Social Networks Analysis and Mining”, founding steering chair of the flagship conference “IEEE/ACM International Conference on Advances in Social Network Analysis and Mining”, and three accompanying symposiums FAB, FOSINT-SI and HI-BI-BI. He is member of the editorial board of the Journal of Information Assurance and Security, Journal of Data Mining and Bioinformatics, Journal of Data Mining, Modeling and Management; he has been guest editor of a number of special issues and edited a number of conference proceedings.
Dr. Alhajj's primary work and research interests focus on various aspects of data science and big datawith emphasis on areas like:(1) scalable techniques and structures for data management and mining, (2) social network analysis with applications in computational biology and bioinformatics, homeland security, etc., (3) sequence analysis with emphasis on domains like financial, weather, traffic, energy, etc., (4) XML, schema integration and re-engineering. He currently leads a large research group of PhD and MSc candidates. He received best graduate supervision award and community service award at the University of Calgary. He recently mentored a number of successful teams, including SANO who ranked first in the Microsoft Imagine Cup Competition in Canada and received KFC Innovation Award in the World Finals held in Russia, TRAK who ranked in the top 15 teams in the open data analysis competition in Canada, Go2There who ranked first in the Imagine Camp competition organized by Microsoft Canada, Funiversewho ranked first in Microsoft Imagine Cup Competition in Canada.
Pr. Hani Hagras
The Computational Intelligence Centre
School of Computer Science and Electronic Engineering
University of Essex, Wivenhoe Park, Colchester, CO4 3SQ, United Kingdom
Professor of Computational Intelligence
Title: "TOWARDS ADVANCED EXPLAINABLE ARTIFICIAL INTELLIGENCE"
Hani Hagras is a Professor of Computational Intelligence, Director of the Computational Intelligence Centre, Head of the Fuzzy Systems Research Group and Head of the Intelligent Environments Research Group in the University of Essex, UK. He is a Fellow of Institute of Electrical and Electronics Engineers (IEEE) and he is also a Fellow of the Institution of Engineering and Technology (IET).
His major research interests are in computational intelligence, notably type-2 fuzzy systems, fuzzy logic, neural networks, genetic algorithms, and evolutionary computation. His research interests also include ambient intelligence, pervasive computing and intelligent buildings. He is also interested in embedded agents, robotics and intelligent control.
He has authored more than 300 papers in international journals, conferences and books. His work has received funding that totalled to about £5 Million in the last five years from the European Union, the UK Technology Strategy Board (TSB), the UK Department of Trade and Industry (DTI), the UK Engineering and Physical Sciences Research Council (EPSRC), the UK Economic and Social Sciences Research Council (ESRC) as well as several industrial companies including. He has also Five industrial patents in the field of computational intelligence and intelligent control.
His research has won numerous prestigious international awards where most recently he was awarded by the IEEE Computational Intelligence Society (CIS), the 2013 Outstanding Paper Award in the IEEE Transactions on Fuzzy Systems and also he has won the 2004 Outstanding Paper Award in the IEEE Transactions on Fuzzy Systems. He was also awarded the 2015 Global Telecommunications Business award for his joint project with British Telecom. In 2016, he was elected as Distinguished Lecturer by the IEEE Computational Intelligence Society. He was also the Chair of the IEEE CIS Chapter that won the 2011 IEEE CIS Outstanding Chapter award. His work with IP4 Ltd has won the 2009 Lord Stafford Award for Achievement in Innovation for East of England. His work has also won the 2011 Best Knowledge Transfer Partnership Project for London and the Eastern Region. His work has also won best paper awards in several conferences including the 2014 and 2006 IEEE International Conference on Fuzzy Systems and the 2012 UK Workshop on Computational Intelligence.
He served as the Chair of IEEE Computational Intelligence Society (CIS) Senior Members Sub-Committee. He served also as the chair of the IEEE CIS Task Force on Intelligent Agents. He is currently the Chair of the IEEE CIS Task Force on Extensions to Type-1 Fuzzy Sets. He is also a Vice Chair of the IEEE CIS Technical Committee on Emergent Technologies. He is a member of the IEEE Computational Intelligence Society (CIS) Fuzzy Systems Technical Committee. He served also as a mement of the IEEE CIS Fellows Committee. He serves also as a member of the IEEE CIS conferences committee.
He is an Associate Editor of the IEEE Transactions on Fuzzy Systems. He is also an Associate Editor of the International Journal of Robotics and Automation.
Prof. Hagras chaired several international conferences where he will act as the Programme Chair of the 2017 IEEE International Conference on Fuzzy Systems. He served as the Co-Chair of the 2014, 2013, 2011 and 2009 IEEE Symposium on Intelligent Agents, and the 2011 IEEE International Symposium on Advances to Type-2 Fuzzy Logic Systems. He was also the General Co-Chair of the 2007 IEEE International Conference on Fuzzy systems.